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Deconstructing word embedding algorithms [article]

Kian Kenyon-Dean, Edward Newell, Jackie Chi Kit Cheung
<span title="2020-11-12">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Given the historical success of word embeddings in NLP, we propose a retrospective on some of the most well-known word embedding algorithms.  ...  In this work, we deconstruct Word2vec, GloVe, and others, into a common form, unveiling some of the common conditions that seem to be required for making performant word embeddings.  ...  Word embedding algorithms We will now introduce the low rank embedder framework for deconstructing word embedding algorithms, inspired by the theory of generalized low rank models (Udell et al., 2016)  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.07013v1">arXiv:2011.07013v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/v7nteje535fvpm47hwo2ttysoq">fatcat:v7nteje535fvpm47hwo2ttysoq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201117010019/https://arxiv.org/pdf/2011.07013v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/66/31/6631b730ac9be6cd0eb7d5b1020f036f8a343ced.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2011.07013v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Deconstructing and reconstructing word embedding algorithms [article]

Edward Newell, Kian Kenyon-Dean, Jackie Chi Kit Cheung
<span title="2019-11-29">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Given the historical success of word embeddings in NLP, we propose a retrospective on some of the most well-known word embedding algorithms.  ...  We demonstrate that these two algorithmic features are sufficient conditions to construct a novel word embedding algorithm, Hilbert-MLE.  ...  Word embedding algorithms We will now introduce the low rank embedder framework for deconstructing word embedding algorithms, inspired by the theory of generalized low rank models (Udell et al., 2016)  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1911.13280v1">arXiv:1911.13280v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rl7wgn3atbh4zmcqzk7t3f3v2q">fatcat:rl7wgn3atbh4zmcqzk7t3f3v2q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200905195905/https://arxiv.org/pdf/1911.13280v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/54/11/5411d9be13f73954715a56f1e25a686bcf296806.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1911.13280v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Deconstructing word embedding algorithms

Kian Kenyon-Dean, Edward Newell, Jackie Chi Kit Cheung
<span title="">2020</span> <i title="Association for Computational Linguistics"> Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) </i> &nbsp; <span class="release-stage">unpublished</span>
Given the historical success of word embeddings in NLP, we propose a retrospective on some of the most well-known word embedding algorithms.  ...  In this work, we deconstruct Word2vec, GloVe, and others, into a common form, unveiling some of the common conditions that seem to be required for making performant word embeddings.  ...  Word embedding algorithms We will now introduce the low rank embedder framework for deconstructing word embedding algorithms, inspired by the theory of generalized low rank models (Udell et al., 2016)  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/2020.emnlp-main.681">doi:10.18653/v1/2020.emnlp-main.681</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nzzhcxva6rhdtc6hqngxphlk7y">fatcat:nzzhcxva6rhdtc6hqngxphlk7y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201213191906/https://www.aclweb.org/anthology/2020.emnlp-main.681.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3e/35/3e35468fe80cfc873be85470fe85714cd727becc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/2020.emnlp-main.681"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Deconstructing Word Embeddings [article]

Koushik Varma Kalidindi
<span title="2019-01-08">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
A review of Word Embedding Models through a deconstructive approach reveals their several shortcomings and inconsistencies.  ...  A new theoretical embedding model, Derridian Embedding, is proposed in this paper.  ...  We henceforth present a deconstructive review of contemporary word embeddings using available literature to clarify certain misconceptions and inconsistencies concerning them.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1902.00551v1">arXiv:1902.00551v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lykupezb3vfxxlngrbl4n7e3y4">fatcat:lykupezb3vfxxlngrbl4n7e3y4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200901085026/https://arxiv.org/ftp/arxiv/papers/1902/1902.00551.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cd/ff/cdff2f8e7b002543ce267413a41fb57249e50818.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1902.00551v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Neural Embedding Allocation: Distributed Representations of Topic Models [article]

Kamrun Naher Keya, Yannis Papanikolaou, James R. Foulds
<span title="2019-09-10">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To get the benefits of these representations simultaneously, we propose a unifying algorithm, called neural embedding allocation (NEA), which deconstructs topic models into interpretable vector-space embeddings  ...  Word embedding models such as the skip-gram learn vector representations of words' semantic relationships, and document embedding models learn similar representations for documents.  ...  Our approach, which we call neural embedding allocation (NEA), is to deconstruct topic models by reparameterizing them using vector-space embeddings.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1909.04702v1">arXiv:1909.04702v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2rl5mhavuff2xahj72cvkntada">fatcat:2rl5mhavuff2xahj72cvkntada</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200914231830/https://arxiv.org/pdf/1909.04702v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/37/d4/37d497812c68fb63cc2dfeea5b21fab75fcf5884.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1909.04702v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Industrial Memories: Exploring the Findings of Government Inquiries with Neural Word Embedding and Machine Learning [chapter]

Susan Leavy, Emilie Pine, Mark T. Keane
<span title="">2019</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
We transform the findings of the Irish government's inquiry into industrial schools and through the use of word embedding, text classification and visualization, present an interactive web-based platform  ...  Techniques such as named entity recognition, word embedding and social network analysis are also used to extract information and unearth new insights from the report.  ...  Feature Extraction with Word Embedding Feature selection was based on the compilation of domain-specific lexicons in order to address the constraint in this project concerning low volumes of available  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-030-10997-4_52">doi:10.1007/978-3-030-10997-4_52</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ebc2mbxa55ga7a35u3ypvbj34m">fatcat:ebc2mbxa55ga7a35u3ypvbj34m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200305163626/https://researchrepository.ucd.ie/bitstream/10197/10321/2/EMCL_LeavyPineKeane.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a0/9d/a09d1686dbf9e8427c48b84fd877995c91051873.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-030-10997-4_52"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Watermarking Generative Information Systems for Duplicate Traceability

Erik Sonnleitner, Josef K�ung
<span title="2013-09-01">2013</span> <i title="Deanship of Scientific Research"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/agc3mek4qngbdaeke6vf5iawfy" style="color: black;">Applied Mathematics &amp; Information Sciences</a> </i> &nbsp;
In order to break words according to its syllables, we utilize the the same algorithm as L A T E X does for breaking words, which is based on Franklin Liang's pioneering dissertation Word Hy-phen-a-tion  ...  Although the original document is of non-relational structure, our algorithm introduces a document deconstruction scheme, which results in the generation of pseudo-tuples.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.12785/amis/070517">doi:10.12785/amis/070517</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5quebyriy5hern5dupucxwvzru">fatcat:5quebyriy5hern5dupucxwvzru</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810111552/http://naturalspublishing.com/files/published/27n1jr346azf36.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1c/db/1cdb3fd5131dbd76a845c1fa4abdb305597ecaf8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.12785/amis/070517"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Machine Reading of Hypotheses for Organizational Research Reviews and Pre-trained Models via R Shiny App for Non-Programmers [article]

Victor Zitian Chen, Felipe Montano-Campos, Wlodek Zadrozny, Evan Canfield
<span title="2021-12-12">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Specifically, we develop NLP models to automatically 1) detect sentences in scholarly documents as hypotheses or not (Hypothesis Detection), 2) deconstruct the hypotheses into nodes (constructs) and links  ...  (causal/associative relationships) (Relationship Deconstruction ), and 3) classify the features of links in terms causality (versus association) and direction (positive, negative, versus nonlinear) (Feature  ...  Facebook's AI Research group created this algorithm to learn word embeddings and perform text classification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2106.16102v3">arXiv:2106.16102v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bpffktfwjzgajfmd27gm6idgdy">fatcat:bpffktfwjzgajfmd27gm6idgdy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211215002851/https://arxiv.org/ftp/arxiv/papers/2106/2106.16102.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/35/25/35259cb274d5564c91a84938b12214a45b84998a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2106.16102v3" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Deconstructing Supertagging into Multi-Task Sequence Prediction

Zhenqi Zhu, Anoop Sarkar
<span title="">2019</span> <i title="Association for Computational Linguistics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ot5sbt27tzdyrhcooo2wxlw7ki" style="color: black;">Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)</a> </i> &nbsp;
Supertagging is a sequence prediction task where each word is assigned a complex syntactic structure called a supertag.  ...  In this thesis, we propose a novel multi-task learning approach for Tree Adjoining Grammar (TAG) supertagging by deconstructing these complex supertags to a set of related but auxiliary sequence prediction  ...  GloVe can encode the semantic similarity between a pair of words in word embedding space.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/k19-1002">doi:10.18653/v1/k19-1002</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/conll/ZhuS19.html">dblp:conf/conll/ZhuS19</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lpnyd63yp5bgjhnyw4hoe6ia4q">fatcat:lpnyd63yp5bgjhnyw4hoe6ia4q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200709172354/http://summit.sfu.ca/system/files/iritems1/20297/etd20800.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c1/1a/c11a2bc6c1d7478baaec01ac5731d326837e8578.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/k19-1002"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Action Assembly: Sparse Imitation Learning for Text Based Games with Combinatorial Action Spaces [article]

Chen Tessler, Tom Zahavy, Deborah Cohen, Daniel J. Mankowitz, Shie Mannor
<span title="2020-02-09">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Specifically, we introduce a new compressed sensing algorithm, named IK-OMP, which can be seen as an extension to the Orthogonal Matching Pursuit (OMP).  ...  We propose a computationally efficient algorithm that combines compressed sensing with imitation learning to solve text-based games with combinatorial action spaces.  ...  We proposed a CS algorithm variant of OMP which we have called Integer K-OMP (IK-OMP) and demonstrated that it can deconstruct a sum of word embeddings into the individual BoW that make up the embedding  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.09700v3">arXiv:1905.09700v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vdepqapmajdoplcv3glg73dtlq">fatcat:vdepqapmajdoplcv3glg73dtlq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200909164215/https://arxiv.org/pdf/1905.09700v3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/51/9a/519af73e3c362d475167918a3e237dc01fbc5565.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1905.09700v3" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Deconstructing Legal Text_Object Oriented Design in Legal Adjudication [article]

Megan Ma, Dmitriy Podkopaev, Avalon Campbell-Cousins, Adam Nicholas
<span title="2020-09-13">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The project, therefore, tests translation by deconstructing sentences from existing legal judgments to their constituent factors.  ...  In the context of computer engineering, the translation of legal text to algorithmic form is seemingly direct. In large part, law may be a ripe field for expert systems and machine learning.  ...  See Jason Brownlee, What are Word Embeddings for Text?  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.06054v1">arXiv:2009.06054v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/h45cmonyb5favavzt477iht42u">fatcat:h45cmonyb5favavzt477iht42u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201003200203/https://arxiv.org/ftp/arxiv/papers/2009/2009.06054.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.06054v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Avant-gardes and the Aleph System: an artistic interface for digital arts

Pablo Gobira
<span title="">2018</span> <i title="Coimbra University Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gyfqjdux65aixliophyazmqgfy" style="color: black;">MatLit : Materialidades da Literatura</a> </i> &nbsp;
The focus of these artists was the word and its deconstruction. The sound of the word, in this process of deconstruction, was valued.  ...  TH E AL E PH S YS T EM The Aleph System is an algorithm that works by focusing on a poem or poems. The poem is operated by the algorithm based on the identification of its letters and words.  ...  In case of the installation Look at yourself, spatialization happens when the interactor's head movements (axes X, Y, Z) are recognized by the algorithm as inputs that trigger outputs.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14195/2182-8830_6-3_14">doi:10.14195/2182-8830_6-3_14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/l4cexntzlvfvpliou4r7lbyrom">fatcat:l4cexntzlvfvpliou4r7lbyrom</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200709094601/https://digitalis-dsp.uc.pt/bitstream/10316.2/44389/1/Avant-gardes_and_the_Aleph_system.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/97/ff/97fff3e0ba9c09465c5f8ced904ee5eb10e52d0a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14195/2182-8830_6-3_14"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Deconstructing Complex Search Tasks: a Bayesian Nonparametric Approach for Extracting Sub-tasks

Rishabh Mehrotra, Prasanta Bhattacharya, Emine Yilmaz
<span title="">2016</span> <i title="Association for Computational Linguistics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/d5ex6ucxtrfz3clshlkh3f6w2q" style="color: black;">Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies</a> </i> &nbsp;
We jointly leverage insights from Bayesian nonparametrics and word embeddings to identify and extract sub-tasks from a given collection of ontask queries.  ...  We train a skip-gram word embeddings model where a query term is used as an input to a log-linear classifier with continuous projection layer and words within a certain window before and after the words  ...  We enrich our non-parametric model by working in the vector embedding space and propose a word-embedding based distance measure (Kusner et al., 2015) to encode query distances for efficient sub-task  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/n16-1073">doi:10.18653/v1/n16-1073</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/naacl/MehrotraBY16.html">dblp:conf/naacl/MehrotraBY16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3wloshu4f5bltp7rq54uaey52a">fatcat:3wloshu4f5bltp7rq54uaey52a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180605085338/http://aclweb.org/anthology/N16-1073" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/52/94/52941e8d297dd45885c6f481430f02aa9a7f48a3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/n16-1073"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Security Implications for Ultra-Low Power Configurable SoC FPAA Embedded Systems

Jennifer Hasler, Sahil Shah
<span title="2018-06-05">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dsgk7nhfgbdvdpo65fxkqjgjr4" style="color: black;">Journal of Low Power Electronics and Applications</a> </i> &nbsp;
Embedded FPAA devices have both positive Security attributes, as well as potential vulnerabilities.  ...  The paper concludes with summarizing key improvements for secure ultra-low power embedded FPAA devices.  ...  All of the groups developed clustering algorithms to assist with grouping and identifying the resulting circuits.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jlpea8020017">doi:10.3390/jlpea8020017</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2svitnjf5basxjp2lwaygutrde">fatcat:2svitnjf5basxjp2lwaygutrde</a> </span>
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Artificial intelligence for ocean science data integration: current state, gaps, and way forward

Tomer Sagi, Yoav Lehahn, Koby Bar
<span title="2020-05-15">2020</span> <i title="University of California Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jsxqydup4nambeo6atfp7ufiaq" style="color: black;">Elementa: Science of the Anthropocene</a> </i> &nbsp;
To test the hypothesis that specific word embedding could improve NER algorithms on the task of identifying oceanic entities in texts, we trained custom word vec-tors.  ...  In this evaluation, we use the Flair NER algorithm (Akbik et al., 2018) , which is based on a word embedding technique as well.  ...  The deconstruction of a DI process in ocean science as portrayed in Figure 4 was performed jointly by T.S. and Y.L.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1525/elementa.418">doi:10.1525/elementa.418</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sglafbad2fhcteq7hsyalgwzo4">fatcat:sglafbad2fhcteq7hsyalgwzo4</a> </span>
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